PerfSPEC Learning Phase

Based in PrefSPEC: Performance Profiling-based Proactive Security Policy Enforcement for Containers document presented in [1], thir repository contains source files used to generate and process data.

Main Reference: PrefSPEC document as White paper

Presentación in Spanish

How to install covers basic enviroment,tools, and recommendations.

PerfSPEC

[!NOTE] With PerfSPEC Security Policies can be managed / watched in Proactive mode by using ranking, learning and profiles for safetiness and performance.

has three phases:

Ranking
Learning
Runtime

This repository is focused in Learning phase with attention on:

Event logs info load and process
Predictive learning model

Note: It is considered that event data collection in raw-audit-logs.log.xz are realistic and representative to simulate administrative operations.

Files

raw-audit-logs.log contains raw Kubernetes audit logs collected using the audit-policy.yaml audit policy.

Tools are distributed in directories:

As some tasks can be used in Python or Rust there are or will be directories for each programming languge inside directories tasks.

Each task/programming-language use a common data directory where processing output files is generated.

Collect data

If you wish to collect your own dataset, there are several source files that might help:

collect/collect.py is a script to trigger the installation and uninstallation of public Helm repositories.
collect/helm-charts.json is a backup of Helm charts used at the time of the collection.

Process data

Learning

Reference

[1]: H. Kermabon-Bobinnec et al., "PerfSPEC: Performance Profiling-based Proactive Security Policy Enforcement for Containers," in IEEE Transactions on Dependable and Secure Computing, doi: 10.1109/TDSC.2024.3420712.

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